Modeling and Feedback Control for Resource Allocation and Performance Analysis in Container Terminals

Alessandri, A.; Cervellera, Cristiano; Cuneo, M.; Gaggero, Mauro; Soncin, Giuseppe

doi:10.1109/tits.2008.2006737

Cited by 52 publications

(40 citation statements)

References 22 publications

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“…In line with previous works (Alessandri et al, 2007(Alessandri et al, , 2008, we introduce a dynamic model to describe the flows of containers that enter or leave a maritime terminal upon the arrival of carriers, or that are scheduled for departure aboard other carriers, respectively. In practice, it is a system composed of container queues, each served by specific transfer resources.…”

Section: An Overview Of the Operations Accomplished In A Maritime Termentioning

confidence: 99%

“…Such difficulty arises particularly when a model is used to devise a management strategy for a container terminal in real time. In this paper, in line with previous works (see Alessandri et al, 2007Alessandri et al, , 2008, a novel approach is proposed that is based on a nonlinear discrete-time dynamic model of the terminal activities, and consists in optimising the container flows by using a limited amount of resources (for example, cranes and other transfer machines). This model allows one to search for an optimal allocation of the resources that minimises a given performance index so as to improve efficiency and increase economic benefit.…”

mentioning

confidence: 99%

“…The contributions of this paper lie in both modelling and control to manage the logistics operations, as a generalisation of the results reported by Alessandri et al (2007Alessandri et al ( , 2008. In Alessandri et al (2007), a linear discrete-time model and a linear cost function are proposed, and the simplex method is applied to control the flows of containers through a typical intermodal terminal.…”

mentioning

confidence: 99%

“…It is worth noting that, in both cases, the predictive control turns out to be an evolution of the one-step-ahead control approach proposed by Alessandri et al (2008), to which it can be reduced by taking the control horizon equal to one.…”

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confidence: 99%

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Management of logistics operations in intermodal terminals by using dynamic modelling and nonlinear programming

et al. 2009

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The increase in efficiency of container terminals is addressed via an approach based on the optimisation of logistics operations. Toward this end, a discrete-time dynamic model of the various flows of containers that are inter-modally routed from arriving carriers to carriers ready for departure is proposed. On the basis of such a model, the decisions on the allocation of the available handling resources inside a container terminal are made according to the predictive-control approach by minimising a performance cost function over a forward horizon from the current time instant. Since both the dynamic equations and the cost function are in general nonlinear and since binary variables are used to model the departure or stay of a carrier, such decisions result from the on-line solution of a mixed-integer nonlinear programming problem at each time step. To solve this problem, two techniques are proposed that have to deal explicitly with the binary variables and with the nonlinearities of the model and the cost function. The first relies on the application of a standard branch-and-bound algorithm. The second is based on the idea of treating the decisions associated with the binary variables as step functions. Simulation results are reported to illustrate the pros and cons of such methodologies in a case study. Maritime Economics & Logistics (2009) 11, 58–76. doi:10.1057/mel.2008.24

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Section: An Overview Of the Operations Accomplished In A Maritime Termentioning

confidence: 99%

mentioning

confidence: 99%

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confidence: 99%

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confidence: 99%

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Management of logistics operations in intermodal terminals by using dynamic modelling and nonlinear programming

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“…However, they lack a general approach considering all terminal operations simultaneously. The control field has also done research in this area applying classic control techniques and assuming undistinguished containers [2,7,8]. The ability to distinguish containers is relevant to network operation because it creates the possibility to group them according their features.…”

Section: Introductionmentioning

confidence: 99%

Efficient Operations at Intermodal Terminals Using a Multi-agent System

Hipólito

Nabais

Botto

2016

Lecture Notes in Electrical Engineering

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Transport networks are large-scale complex systems whose objective is to deliver cargo at a specific time and at a specific location. Ports and intermodal container terminals behave as exchange hubs where containers are moved from a transport modality to a different one. Terminal operations management arise as a need to face the exponentially growth of the container traffic in the last few years. In this paper the Extended Formulation of the MPC is presented. This formulation accounts for the variation of the control action to reduce not only the amount of actions but to perform a wise and efficient use of handling resources. This formulation is based on the decomposition of the control action. The Extended Formulation is applied to a simulation case study based on a long-term scheduled scenario and compared with the Basic Formulation.

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Nonlinear Model Predictive Control for Resource Allocation in the Management of Intermodal Container Terminals

Alessandri

Cervellera

Cuneo

et al. 2009

Nonlinear Model Predictive Control

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Modeling and Feedback Control for Resource Allocation and Performance Analysis in Container Terminals

Cited by 52 publications

References 22 publications

Management of logistics operations in intermodal terminals by using dynamic modelling and nonlinear programming

Management of logistics operations in intermodal terminals by using dynamic modelling and nonlinear programming

Efficient Operations at Intermodal Terminals Using a Multi-agent System

Nonlinear Model Predictive Control for Resource Allocation in the Management of Intermodal Container Terminals

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